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Examples of Computerized Markov Analysis Tools

Because of the complexity and computational difficulty of Markov methods, computer solutions are essentially mandatory. There are a number of computerized Markov tools available to perform these types of analyses. A brief discussion of two of these tools follows.

SHARPE Symbolic Hierarchical Automated Reliability and Performance Evaluator [6]. This is a tool for specifying and analyzing performance, reliability and performability models. It is a toolkit that provides a specification language and solution methods for most of the commonly used model types for performance, reliability, and performability modeling. Model types include combinatorial one such as fault-trees and queuing networks and state-space ones such as Markov and semi-Markov reward models as well stochastic Petri nets. Steady-state, transient and interval measures can be computed. Output measures of a model can be used as parameters of other models. This facilitates the hierarchical combination of different model types. To increase the usability of this modeling tool, a graphical user interface (GUI) for SHARPE has been implemented. The SHARPE GUI implements eight interchangeable modeling description techniques for reliability engineering: fault trees, Markov chains, reliability block diagrams, reliability graphs, generalized stochastic Petri nets, product queuing networks, multi-chain product form queuing networks and task graphs. In the future, all the modeling description techniques contained in SHARPE will be available in the GUI (phase mission, multicomponents fault trees, semi-Markov chains). The hierarchy feature is also implemented in the GUI. Java is the language chosen for GUI implementation.

MKV Version 3.0 Markov Analysis Software. This program also analyses non-homogeneous processes by allowing timedependent transition rates to be defined. Systems with timedependent transition rates are strictly non-Markovian, however the addition of this facility in the MKV program allows certain types of aging processes to be modeled. MKV calculates a wide range of system parameters during the integration process. These parameters are Unavailability, Availability, Unreliability, Reliability, Failure frequency (unconditional failure intensity), Repair frequency (unconditional repair intensity), Conditional failure intensity, Conditional repair intensity, Number of expected failures, Number of expected repairs, Mean unavailability over lifetime, Mean availability over lifetime, Expected total downtime over lifetime and Expected total uptime over lifetime. Markov analysis provides a means of analyzing the reliability and availability of systems whose components exhibit strong dependencies. Other systems analysis methods (such as the Kinetic Tree Theory method generally employed in fault tree analysis) often assume component independence, which may lead to optimistic predictions for the system availability and reliability parameters.